A typical prior art sensor network used for remote health monitoring is depicted in FIG. 1. The two main components are sensor block 200 and computing device 300, which here is an intelligent backend device. Sensor block 200 typically is a medical device for obtaining data from a patient, such as an electroencephalograph, cardiotocograph, or other device. Sensor block 200 comprises an amplifier (100), an analog-to-digital (ADC) conversion block 101, a post processor 102, a transmitter 103, and an antenna 104. It is to be understood that other sensor blocks similar to sensor block 200 can be used with the same computing device 300. For brevity's sake, only sensor block 200 is depicted in FIG. 1.
Computing device 300 may be a PC, server or any product with processing capabilities. Sensor block 200 obtains data from a patient, such as brain signals, heart signals, temperature, etc. using electrodes or other means, amplifies the sensed analog signals using amplifier 100, converts the analog signal into digital data using analog-to-digital conversion block 101, and processes the raw digital data using post processor 102, which can packetize the data, add headers, encrypt the data, and perform other known techniques. The packetized data is then send to computing device using transmitter 103 and antenna 104 over network 105. Network 105 can be a wireless network, a hardwired network, or a combination of the two.
The prior art sensor network of FIG. 1 has several drawbacks. First, sensor block 200 consumes a substantial amount of power. This is mainly because the sensor runs at full speed. As an example, if sensor block 200 is generating electroencephalography (EEG) signals, the signal bandwidth will include frequencies up to 1 KHz, and analog-to-digital converter 20 will need to perform sampling of the analog signal at a rate of at least 2 KHz (which is the Nyquist rate of the highest frequency in the signal). In addition, transmitter 103 will needs to transmit at that same rate, 2 KHz. In a typical medical device, transmitter 103 can consume 80% of the total power consumed by the device. For some applications where packetization and encryption needs are large, the post processing block may be the power bottleneck since it too runs at or above the Nyquist rate.
Second, computing device 300 needs to store all the data it receives and process it. Typically the computing device 300 will process the received data and take actions in response to the data (for example, begin an audio alarm). It can be appreciated that computing device 300 performs a substantial amount of data analysis and typically will generate a user interface that creates a visual display of the data obtained by sensor block 200. The large amount of data leads to high storage costs and consumes a significant amount of processing time and power.
Third, security is a major implementation drain. Sending data over wireless links requires some mode of encryption, all of which require extra power and resources.
What is needed is an improved sensor network that with sensor blocks that transmit less data and a computing device that operates on less data than in prior art sensor networks.